Using an index-based approach to assess the population-level appropriateness of empirical antibiotic therapy.

OBJECTIVES: The population-level appropriateness of empirical antibiotic therapy can be conventionally measured by ascertainment of treatment coverage. This method involves a complex resource-intensive case-by-case assessment of the prescribed antibiotic treatment and the resistance of the causative microorganism. We aimed to develop an alternative approach based, instead, on the use of routinely available surveillance data. METHODS: We calculated a drug effectiveness index by combining three simple aggregated metrics: relative frequency of aetiological agents, level of resistance and relative frequency of antibiotic use. To evaluate the applicability of our approach, we used this metric to estimate the population-level appropriateness of guideline-compliant and non-guideline-compliant empirical treatment regimens in the context of the Dutch national guidelines for complicated urinary tract infections. RESULTS: The drug effectiveness index agrees within 5% with results obtained with the conventional approach based on a case-by-case ascertainment of treatment coverage. Additionally, we estimated that the appropriateness of 2008 antibiotic prescribing regimens would have declined by up to 4% by year 2011 in the Netherlands due to the emergence and expansion of antibiotic resistance. CONCLUSIONS: The index-based framework can be an alternative approach to the estimation of point values and counterfactual trends in population-level empirical treatment appropriateness. In resource-constrained settings, where empirical prescribing is most prevalent and comprehensive studies to directly measure appropriateness may not be a practical proposition, an index-based approach could provide useful information to aid in the development and monitoring of antibiotic prescription guidelines.

Efficient national surveillance for health-care-associated infections.

BACKGROUND: Detecting novel healthcare-associated infections (HCAI) as early as possible is an important public health priority. However, there is currently no evidence base to guide the design of efficient and reliable surveillance systems. Here we address this issue in the context of a novel pathogen spreading primarily between hospitals through the movement of patients. METHODS: Using a mathematical modelling approach we compare the current surveillance system for a HCAI that spreads primarily between hospitals due to patient movements as it is implemented in Scotland with a gold standard to determine if the current system is maximally efficient or whether it would be beneficial to alter the number and choice of hospitals in which to concentrate surveillance effort. RESULTS: We validated our model by demonstrating that it accurately predicts the risk of meticillin-resistant Staphylococcus aureus bacteraemia cases in Scotland. Using the 29 (out of 182) sentinel hospitals that currently contribute most of the national surveillance effort results in an average detection time of 117 days. A reduction in detection time to 87 days is possible by optimal selection of 29 hospitals. Alternatively, the same detection time (117 days) can be achieved using just 22 optimally selected hospitals. Increasing the number of sentinel hospitals to 38 (teaching and general hospitals) reduces detection time by 43 days; however decreasing the number to seven sentinel hospitals (teaching hospitals) increases detection time substantially to 268 days. CONCLUSIONS: Our results show that the current surveillance system as it is used in Scotland is not optimal in detecting novel pathogens when compared to a gold standard. However, efficiency gains are possible by better choice of sentinel hospitals, or by increasing the number of hospitals involved in surveillance. Similar studies could be used elsewhere to inform the design and implementation of efficient national, hospital-based surveillance systems that achieve rapid detection of novel HCAIs for minimal effort.

Disease transmission on fragmented contact networks: livestock-associated Methicillin-resistant Staphylococcus aureus in the Danish pig-industry.

Animal trade in industrialised livestock-production systems creates a complex, heterogeneous, contact network that shapes between-herd transmission of infectious diseases. We report the results of a simple mathematical model that explores patterns of spread and persistence of livestock-associated Methicillin-resistant Staphylococcus aureus (LA-MRSA) in the Danish pig-industry associated with this trade network. Simulations show that LA-MRSA can become endemic sustained by animal movements alone. Despite the extremely low predicted endemic prevalence, eradication may be difficult, and decreasing within-farm prevalence, or the time it takes a LA-MRSA positive farm to recover a negative status, fails to break long-term persistence. Our results suggest that a low level of non-movement induced transmission strongly affects MRSA dynamics, increasing endemic prevalence and probability of persistence. We also compare the model-predicted risk of 291 individual farms becoming MRSA positive, with results from a recent Europe-wide survey of LA-MRSA in holdings with breeding pigs, and find a significant correlation between contact-network connectivity properties and the model-estimated risk measure.

Strong and electroweak corrections to the production of a Higgs boson+2 jets via weak interactions at the Large Hadron Collider.

Radiative corrections of strong and electroweak interactions are presented at next-to-leading order for the production of a Higgs boson plus two hard jets via weak interactions at the CERN Large Hadron Collider. The calculation includes all weak-boson fusion and quark-antiquark annihilation diagrams as well as the corresponding interferences. The electroweak corrections, which are discussed here for the first time, reduce the cross sections by 5% and thus are of the same order of magnitude as the QCD corrections.